Digital communication receivers must sample an analog waveform and then reliably detect the sampled data. Signals arriving at a receiver are typically corrupted by intersymbol interference (ISI), crosstalk, echo, and other noise. In order to compensate for such channel distortions, communication receivers often employ well-known equalization techniques. For example, zero equalization or decision-feedback equalization (DFE) techniques (or both) are often employed. Such equalization techniques are widely-used for removing intersymbol interference and to improve the noise margin. See, for example, R. Gitlin et al., Digital Communication Principles, (Plenum Press, 1992) and E. A. Lee and D. G. Messerschmitt, Digital Communications, (Kluwer Academic Press, 1988), each incorporated by reference herein. Generally, zero equalization techniques equalize the pre-cursors of the channel impulse response and decision-feedback equalization equalizes the post cursors of the channel impulse response.
In one typical DFE implementation, a received signal is sampled and compared to one or more thresholds to generate the detected data. A DFE correction is applied in a feedback fashion to produce a DFE corrected signal. The addition/subtraction, however, is considered to be a computationally expensive operation. Thus, a variation of the classical DFE technique, often referred to as Spatial DEE, eliminates the analog adder operation by sampling the received signal using two (or more) vertical slicers that are offset from the common mode voltage. The two slicers are positioned based on the results of a well-known Least Mean Square (LMS) algorithm. One slicer is used for transitions from a binary value of 0 and the second slicer is used for transitions from a binary value of 1. The value of the previous detected bit is used to determine which slicer to use for detection of the current bit. For a more detailed discussion of Spatial DFE techniques, see, for example, Yang and Wu, “High-Performance Adaptive Decision Feedback Equalizer Based on Predictive Parallel Branch Slicer Scheme,” IEEE Signal Processing Systems 2002, 121-26 (2002), incorporated by reference herein.
A communication channel typically exhibits a low pass effect on a transmitted signal. Conventional channel compensation techniques attempt to open the received data eye that has been band limited by the low pass channel response. Thus, the various frequency content of the signal will suffer different attenuation at the output of the channel. Generally, the higher frequency components of a transmitted signal are impaired more than the lower frequency components.
In many DFE applications, the Least Mean Square algorithm positions the vertical slicers by evaluating an error term for a known receive data stream. Such known receive data streams, however, are not always available. In addition, such techniques often converge to a local minimum, producing sub-optimal results. In some cases, such techniques can converge to he wrong adapted latch position values. A need exists for improved methods and apparatus for decision-feedback equalization with global minimum convergence. A further need exists for methods and apparatus that position one or more DFE latches using global minimum convergence and an evaluation of the incoming data eye.